Retinal image enhancement based on the human visual system

Kamel Belkacem-Boussaid; Balaji Raman; Gilberto Zamora; Yeshwanth Srinivasan; Sven-Erick Bursell

doi:10.1117/12.653816

20 March 2006 Retinal image enhancement based on the human visual system

Kamel Belkacem-Boussaid, Balaji Raman, Gilberto Zamora, Yeshwanth Srinivasan, Sven-Erick Bursell

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61446J (2006) https://doi.org/10.1117/12.653816
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

Improving the quality of gray level images continues to be a challenging task, and the challenge increases for color images due to the interaction of multiple parameters within a scene. Each color plane or wavelength constitutes an image by itself, and its quality depends on many parameters such as absorption, reflectance or scattering of the object with the lighting source. Non-uniformity of the lighting, optics, electronics of the camera, and even the environment of the object are sources of degradation in the image. Therefore, segmentation and interpretation of the image may become very difficult if its quality is not enhanced. The main goal of the present work is to demonstrate image processing algorithm that is inspired from some concepts of the Human Visual System (HVS). HVS concepts have been widely used in gray level image enhancement and here we show how they can be successfully extended to color images. The resulting Multi-Scale Spatial Decomposition (MSSD) is employed to enhance the quality of color images. Of particular interest for medical imaging is the enhancement of retinal images whose quality is extremely sensitive to imaging artifacts. We show that our MSSD algorithm improves the readability and gradeability of retinal images and quantify such improvements using both subjective and objective metrics of image quality.

Citation Download Citation

Kamel Belkacem-Boussaid, Balaji Raman, Gilberto Zamora, Yeshwanth Srinivasan, and Sven-Erick Bursell "Retinal image enhancement based on the human visual system", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61446J (20 March 2006); https://doi.org/10.1117/12.653816

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